Apparatus and method for generating algorithm modules based on a plurality of published guidelines using machine learning

Abstract

An apparatus and method for training a machine learning model to receive a plurality of subject data associated with a particular subject, wherein the plurality of subject data comprises structured data and unstructured data, receive a plurality of guidelines, instantiate a machine learning model, wherein the machine learning model is configured to receive the plurality of guidelines as an input and output a plurality of algorithm modules, process the plurality of subject data, wherein processing the plurality of subject data comprises instantiating at least a large language model, wherein the at least a large language model is configured to generate processed subject data by processing the plurality of subject data, generate, using the machine learning model, an output based on the processed data and the plurality of algorithm modules, and display the output, using a client device, through a graphical user interface.

1 . An apparatus for generating algorithm modules based on a plurality of published guidelines using a machine learning model, wherein the apparatus comprises:
 at least a computing device, wherein the computing device comprises:
 a memory; and 
 at least a processor communicatively connected to the memory, wherein the memory contains instructions configuring the at least a processor to:
 receive a plurality of subject data associated with a particular subject, wherein the plurality of subject data comprises structured data and unstructured data; 
 receive a plurality of guidelines comprising Guided Directed Medical Therapy (GDMT) published principles; 
 instantiate a rule large language model, wherein the rule large language model is configured to receive the plurality of guidelines as an input and output a plurality of algorithm modules based on the plurality of guidelines; 
 process the plurality of subject data, wherein processing the plurality of subject data comprises instantiating at least a language processing model, wherein the at least a language processing model is configured to generate processed subject data by processing the plurality of subject data; 
 generate a plurality of recommendations to treat an identified condition of the particular subject based on the processed subject data and the plurality of algorithm modules, wherein at least a recommendation of the plurality of recommendations comprises a confidence score generated as a function of a classifier model; and 
 display the plurality of recommendations, using a client device, through a graphical user interface. 
 
   
     
     
         2 . The apparatus of  claim 1 , wherein the plurality of subject data comprises electronic health records and multimodal data. 
     
     
         3 . The apparatus of  claim 1 , wherein the plurality of algorithm modules comprises one or more decision tree data structures. 
     
     
         4 . The apparatus of  claim 1 , wherein the plurality of algorithm modules comprises a validation model, wherein the validation model is configured to verify whether the plurality of subject data is valid. 
     
     
         5 . The apparatus of  claim 1 , wherein the plurality of algorithm modules comprises a classifier model, wherein the classifier model is configured to determine whether the particular subject is associated with a particular condition. 
     
     
         6 . The apparatus of  claim 1 , wherein processing the plurality of subject data comprises:
 processing the structured data and the unstructured data of the plurality of subject data using a large language model of the at least a language processing model; and   processing the structured data and the unstructured data of the plurality of subject data using a natural language processing algorithm of the at least a language processing model.   
     
     
         7 . The apparatus of  claim 1 , wherein the at least a recommendation of the plurality of recommendations is associated with a therapy to treat a condition. 
     
     
         8 . The apparatus of  claim 1 , wherein the memory contains instructions configuring the at least a processor to:
 identify a plurality of subject data requirements as a function of the plurality of algorithm modules;   determine whether each of the plurality of subject data requirements is computable or not computable as a function of the plurality of subject data;   determine a query as a function of a subject data requirement that is determined to be not computable; and   display the query on the client device.   
     
     
         9 . The apparatus of  claim 1 , wherein the graphical user interface comprises a prompt window, wherein the prompt window is configured to receive a user input. 
     
     
         10 . The apparatus of  claim 9 , wherein the language processing model is further configured to:
 receive the user input;   process the user input; and   generate processed data.   
     
     
         11 . A method for generating algorithm modules based on a plurality of published guidelines using a machine learning model, wherein the method comprises:
 receiving a plurality of subject data associated with a particular subject, wherein the plurality of subject data comprises structured data and unstructured data;   receiving a plurality of guidelines comprising Guided Directed Medical Therapy (GDMT) published principles;   instantiating a rule large language model, wherein the rule large language model is configured to receive the plurality of guidelines as an input and output a plurality of algorithm modules based on the plurality of guidelines;   processing the plurality of subject data, wherein processing the plurality of subject data comprises instantiating at least a language processing model, wherein the at least a language processing model is configured to generate processed subject data by processing the plurality of subject data;   generating a plurality of recommendations to treat an identified condition of the particular subject based on the processed subject data and the plurality of algorithm modules, wherein at least a recommendation of the plurality of recommendations comprises a confidence score generated as a function of a classifier model; and   displaying the plurality of recommendations, using a client device, through a graphical user interface.   
     
     
         12 . The method of  claim 11 , wherein the plurality of subject data comprises electronic health records and multimodal data. 
     
     
         13 . The method of  claim 11 , wherein the plurality of algorithm modules comprises one or more decision tree data structures. 
     
     
         14 . The method of  claim 11 , wherein the plurality of algorithm modules comprises a validation model, wherein the validation model is configured to verify whether the plurality of subject data is valid. 
     
     
         15 . The method of  claim 11 , wherein the plurality of algorithm modules comprises a classifier model, wherein the classifier model is configured to determine whether the particular subject is associated with a particular condition. 
     
     
         16 . The method of  claim 11 , wherein processing the plurality of subject data comprises:
 processing the structured data and the unstructured data of the plurality of subject data using a large language model of the at least a language processing model; and   processing the structured data and the unstructured data of the plurality of subject data using a natural language processing algorithm of the at least a language processing model.   
     
     
         17 . The method of  claim 11 , wherein the at least a recommendation of the plurality of recommendations is associated with a therapy to treat a condition. 
     
     
         18 . The method of  claim 11 , further comprising:
 identifying, using the at least a processor, a plurality of subject data requirements as a function of the plurality of algorithm modules;   determining, using the at least a processor, whether each of the plurality of subject data requirements is computable or not computable as a function of the plurality of subject data;   determining, using the at least a processor, a query as a function of a subject data requirement that is determined to be not computable; and   displaying, using the at least a processor, the query on the client device.   
     
     
         19 . The method of  claim 11 , wherein the graphical user interface comprises a prompt window, wherein the prompt window is configured to receive a user input. 
     
     
         20 . The method of  claim 19 , wherein the language processing model is further configured to:
 receive the user input;   process the user input; and   generate processed data.